Acquisition decisions, including whether acquiring companies should pay with stock or cash and whether the financing decision matters to target companies, are often complex and difficult. The authors explore these and other issues by devising an acquisition finance prediction model. The financing decision can affect the capital structure and have a long-term impact on the profitability of the merged entity.

Justification for a particular means of payment (stock versus cash) is found to be a function of the acquirer’s share valuation in its effort to move to an ideal capital structure. Using the developed prediction model, the authors demonstrate that it is rare for an acquirer to make a stock financing decision that cannot be justified and that target firms will accept a payment in overvalued stock as long as the payment choice can be justified. The authors also observe asymmetry in prediction errors, which is caused by the fact that firms are far more likely to pay cash when the model predicts the use of equity than they are to change from a predicted cash payment to a stock payment.

In addition to investigating the model’s financing prediction ability, the authors examine the long-term excess returns that result from it. They demonstrate that cash-financed acquisitions are more likely to result in long-term positive excess returns when the economics of the transaction predict equity financing.

By analyzing other control variables in the acquisition finance prediction model, the authors find that the acquiring firm is more likely to make a cash offer when it is a tender offer and when there are multiple bidders. The main finding, however, is that market timing is possible in acquisitions as long as they are driven by fundamental economic motives.

Students of corporate finance—mergers and acquisitions in particular—would find the behavioral implications of this research relevant to their work, as would practitioners who advise on either side of an acquisition as well as securities analysts.

To develop their model, the authors build on relevant literature. For their analysis, they draw on transactions contained in the Securities Data Corporation’s mergers and acquisitions database over the 25-year period from 1 January 1980 to 31 December 2005. The resulting sample includes 2,978 transactions. For a transaction to be included, it must have been completed, both the acquirer and target must be US companies, the acquirer may not be a financial services or real estate concern, and the bidder must have acquired at least half of the target. Financial statement data are from Compustat, and stock market data are from the Center for Research in Securities Prices.

The authors use their results to determine whether acquisition finance is motivated by fundamentals or market timing. They build pro forma balance sheets under a stock and cash payment scenario, comparing pro forma leverage with the optimal amount for the combined entity. They also use the literature to make their model robust to a number of control variables specific to acquisition finance, including illiquidity, the size of the target relative to that of the bidder, competing bids and toeholds, and governance structure.

Both short-term announcements and long-term returns are considered. The former could reflect the effect of the financing decision on firm value but may also be driven by shorter-term considerations (arbitrageurs’ shorting of the acquirer’s shares). Therefore, longer-term results are critical to the analysis.

The authors develop and implement a prediction model to determine what underlies acquiring companies’ decisions regarding acquisition financing, taking into account market timing as well as fundamentals of capital structure and acquisition finance. For the sample in question, which is consistent with that of other studies and robust to quality controls, it correctly predicts this decision 89% of the time. It would be interesting to see how to develop a similar methodology for such other corporate actions as spinoffs, stock buybacks, and rights issues. The financing decision is as much behavioral as it is financial.